Somoray, Klaire, and Miller, Dan J. (2023) Providing detection strategies to improve human detection of deepfakes: An experimental study. Computers in Human Behaviour, 149. 107917.

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Abstract

Deepfake videos are becoming more pervasive. In this preregistered online experiment, participants (N = 454, Mage = 37.19, SDage = 13.25, males = 57.5%) categorize a series of 20 videos as either real or deepfake. All participants saw 10 real and 10 deepfake videos. Participants were randomly assigned to receive a list of strategies for detecting deepfakes based on visual cues (e.g., looking for common artifacts such as skin smoothness) or to act as a control group. Participants were also asked how confident they were that they categorized each video correctly (per video confidence) and to estimate how many videos they correctly categorized out of 20 (overall confidence). The sample performed above chance on the detection activity, correctly categorizing 60.70% of videos on average (SD = 13.00). The detection strategies intervention did not impact detection accuracy or detection confidence, with the intervention and control groups performing similarly on the detection activity and showing similar levels of confidence. Inconsistent with previous research, the study did not find that participants had a bias toward categorizing videos as real. Participants overestimated their ability to detect deepfakes at the individual video level. However, they tended to underestimate their abilities on the overall confidence question.

Item ID:	79985
Item Type:	Article (Research - C1)
ISSN:	1873-7692
Keywords:	Deepfake, Human detection, detection strategies, Accuracy, Confidence
Related URLs:	Author
Copyright Information:	© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Date Deposited:	23 Aug 2023 00:37
FoR Codes:	52 PSYCHOLOGY > 5204 Cognitive and computational psychology > 520406 Sensory processes, perception and performance @ 60% 46 INFORMATION AND COMPUTING SCIENCES > 4608 Human-centred computing > 460899 Human-centred computing not elsewhere classified @ 40%
SEO Codes:	28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences @ 30% 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280121 Expanding knowledge in psychology @ 40% 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280123 Expanding knowledge in human society @ 30%
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